%Generic Algorithm for function f(x1,x2) optimum
clear all;
close all;

%Parameters
Size=80;     %群体大小
G=100;       %终止进化代数
CodeL=10;  
 
umax=2.048;
umin=-2.048;

E=round(rand(Size,2*CodeL));    %Initial Code

%Main Program
for k=1:1:G
    
    time(k)=k;
    
    for s=1:1:Size
        m=E(s,:);
        y1=0;y2=0;
        
        %Uncoding 解码
        m1=m(1:1:CodeL);
        for i=1:1:CodeL
           y1=y1+m1(i)*2^(i-1);
        end
        x1=(umax-umin)*y1/1023+umin;
        m2=m(CodeL+1:1:2*CodeL);
        for i=1:1:CodeL
           y2=y2+m2(i)*2^(i-1);
        end
        x2=(umax-umin)*y2/1023+umin;
        
        F(s)=100*(x1^2-x2)^2+(1-x1)^2;    % F(x1,x2)
    end
    
    Ji=1./F;     %选个体适应度的倒数作为目标函数

    %****** Step 1 : Evaluate BestJ ******
    BestJ(k)=min(Ji);
    
    fi=F;                          %Fitness Function
    [Oderfi,Indexfi]=sort(fi);     %Arranging fi small to bigger
    Bestfi=Oderfi(Size);           %Let Bestfi=max(fi)
    BestS=E(Indexfi(Size),:);      %Let BestS=E(m), m is the Indexfi belong to max(fi)
    bfi(k)=Bestfi;
    
    %****** Step 2 : Select and Reproduct Operation******
       fi_sum=sum(fi);
       fi_Size=(Oderfi/fi_sum)*Size;
       
       fi_S=floor(fi_Size);        %Selecting Bigger fi value
       
       kk=1;
       for i=1:1:Size
          for j=1:1:fi_S(i)        %Select and Reproduce 
           TempE(kk,:)=E(Indexfi(i),:);  
             kk=kk+1;              %kk is used to reproduce
          end
       end
       
    %************ Step 3 : Crossover Operation ************
    pc=0.60;
    n=ceil(20*rand);
    for i=1:2:(Size-1)
        temp=rand;
        if pc>temp                  %Crossover Condition
        for j=n:1:20
            TempE(i,j)=E(i+1,j);
            TempE(i+1,j)=E(i,j);
        end
        end
    end
    TempE(Size,:)=BestS;
    E=TempE;
       
    %************ Step 4: Mutation Operation **************
    %pm=0.001;
    %pm=0.001-[1:1:Size]*(0.001)/Size; %Bigger fi, smaller Pm
    %pm=0.0;    %No mutation
    pm=0.1;     %Big mutation
    
       for i=1:1:Size
          for j=1:1:2*CodeL
             temp=rand;
             if pm>temp                %Mutation Condition
                if TempE(i,j)==0
                   TempE(i,j)=1;
                else
                   TempE(i,j)=0;
                end
            end
          end
       end
       
    %Guarantee TempPop(30,:) is the code belong to the best individual(max(fi))
    TempE(Size,:)=BestS;
    E=TempE;
end
 
Max_Value=Bestfi
BestS
x1
x2
figure(1);
plot(time,BestJ); 
xlabel('Times');ylabel('Best J');
figure(2);
plot(time,bfi);
xlabel('times');ylabel('Best F');
